Image-to-Text
Transformers
PyTorch
Safetensors
vision-encoder-decoder
image-text-to-text
donut
vision
Instructions to use TeeA/Horus-OCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeeA/Horus-OCR with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="TeeA/Horus-OCR")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("TeeA/Horus-OCR") model = AutoModelForImageTextToText.from_pretrained("TeeA/Horus-OCR") - Notebooks
- Google Colab
- Kaggle
Training done
Browse files- tokenizer.json +16 -2
tokenizer.json
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"added_tokens": [
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"id": 0,
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length": 768,
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"strategy": "LongestFirst",
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"stride": 0
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"padding": {
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"strategy": {
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"Fixed": 768
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"direction": "Right",
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"pad_to_multiple_of": null,
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"pad_id": 1,
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"pad_type_id": 0,
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"pad_token": "<pad>"
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},
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"added_tokens": [
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"id": 0,
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